Senior Data Scientist, Clinical Pharmacology Data Analysis and Reporting

Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams rich in diversity. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.

Position Summary

The Senior Data Scientist leverages SAS or R to integrate data from diverse sources for pharmacometric (PMx) analyses, supporting regulatory filings, internal decisions and HA interactions. The individual will prepare analysis-ready data sets for use in NONMEM or NLME by modeling experts for pharmacometric analysis and for non-compartmental analysis (NCA). They will produce tables, listings, and figures, and assist in the preparation of pharmacometric reports and prepare the datasets and definition files for submissions. The Senior Data Scientist will follow rigorous, systematic processes to address deficiencies in source data, ensuring consistent and accurate data compilation across studies by implementing sophisticated algorithms and standard rules to address these issues. The Senior Data Scientist will perform quality control on all deliverables, utilizing various tools.

The Senior Data Scientist is expected to execute all job duties, while also collaborating closely with senior management for guidance and supervision.

Duties/Responsibilities

• Responsible and accountable for high quality PMx analysis datasets and reports across all therapeutic areas. 
• Utilize expert knowledge of SAS or R to integrate clinical data and pharmacokinetic data to prepare analysis datasets for pharmacometric analysis in NONMEM and other modeling tools. 
• Apply solid knowledge of pharmacokinetics, pharmacodynamics, and other scientific areas to partner with experts to integrate data sources efficiently and effectively. 
• Implement sophisticated algorithms to derive complex data sets, and address data issues with supervision. 
• Use visualization software for validation and quality check.
• Prepare submission packages including datasets, tables, listings, and figures, authoring data section of the PMx report, for filing with health authorities and responses to queries from health authorities. 
• Work on outsourced projects. 
• Competence in Python, Spotfire and various Linux/UNIX tools including bash.
• May contribute to continuous improvement initiatives for process efficiencies, including developing Artificial Intelligence/Machine Learning (AI/ML) solutions.
• Stay up to date on all role-based training.

Qualifications

• 2+ years of pharmaceutical industry experience in preparing SAS data sets for analysis. 
• 1+ years’ experience preparing SAS data sets for PMx analysis in NONMEM, NLME, or WinNonLin. 
• Excellent proficiency in SAS or R programming language. 
• Skilled in Python programming.
• Certification in SAS, R or Python.
• Competence in UNIX or Linux, and skill with bash scripting and UNIX filters.  
• Knowledge of pharmacokinetic data, clinical data, NONMEM concepts and data issues with programming NONMEM data sets.  
• Ability to implement sophisticated algorithms to derive complex data sets and address data issues.
• Familiarity with principles of quality control.
• Strong attention to quality and detail, with the ability to detect data anomalies.  
• Excellent interpersonal and communication skills.
• Bachelor’s degree in engineering, science, computer science, mathematics, or statistics.  
• Master’s or higher degree preferred.
• Local and international travel for conferences may be required 5-10% of the time.
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